With the advanced development of camera technology, the amount of data associated with a single frame has grown dramatically. A few years ago camera technology was limited to a few thousand pixels per frame. That number has shot past 10 million pixels per frame on a relatively inexpensive camera and professional still and movie cameras are well beyond 20 million pixels per frame.
This increase in the number of pixels has brought with it breath-taking detail and clarity of both shapes and colors. As the amount of data needed to display a high definition frame has continued to grow, the timing required to display the data on a high definition television has dropped from 10's of milliseconds to less than two milliseconds. The unprecedented clarity and color rendition has driven the increase in the number of pixels that we desire to view.
In order to transfer the now massive amount of data required to identify the Luma (Y), the Chroma blue (Cb), and the Chroma red (Cr) for every pixel in the frame, some reduction in the data must take place. Luma is associated with the brightness value and both Chroma blue (Cb), and the Chroma red (Cr) are associated with the color value. Several techniques have been proposed, which trade a reduction in detail for full color, a reduction in color for more detail, or a reduction in both detail and color. There is yet to be found a balanced approach that can maintain the detail and represent the full color possibilities of each frame.
Thus, a need still remains for video transmission system with color prediction that can minimize the transfer burden while maintaining the full detail and color content of each frame of a video stream. In view of the ever increasing demand for high definition movies, photos, and video clips, it is increasingly critical that answers be found to these problems. In view of the ever-increasing commercial competitive pressures, along with growing consumer expectations and the diminishing opportunities for meaningful product differentiation in the marketplace, it is critical that answers be found for these problems. Additionally, the need to reduce costs, improve efficiencies and performance, and meet competitive pressures adds an even greater urgency to the critical necessity for finding answers to these problems.